Triple
T20387102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cho |
E497986
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Cho Hye-jin
Cho Hye-jin is a Korean individual notable enough to be specifically distinguished as a bearer of the surname Cho.
|
E1479630
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Cho Hye-jin | Statement: [Cho, hasNotableBearer, Cho Hye-jin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cho Hye-jin Context triple: [Cho, hasNotableBearer, Cho Hye-jin]
-
A.
Min Hye-jin
Min Hye-jin is a determined and principled lawyer in the South Korean dark fantasy series "Hellbound," who challenges a powerful cult and supernatural decrees of damnation.
-
B.
Jang Hye-jin
Jang Hye-jin is a South Korean actress best known internationally for her role as the resourceful housekeeper in the Academy Award–winning film "Parasite."
-
C.
Jeong Ji-hyun
Jeong Ji-hyun is a Korean individual whose name is romanized from the Korean name Ji-hyun Jung.
-
D.
Cho Hee-yeon
Cho Hee-yeon is a South Korean educator and academic known for serving as the superintendent of the Seoul Metropolitan Office of Education.
-
E.
Suh Ji-hyun
Suh Ji-hyun is a South Korean individual notable for bearing the Korean surname Suh.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Cho Hye-jin Triple: [Cho, hasNotableBearer, Cho Hye-jin]
Generated description
Cho Hye-jin is a Korean individual notable enough to be specifically distinguished as a bearer of the surname Cho.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cho Hye-jin Target entity description: Cho Hye-jin is a Korean individual notable enough to be specifically distinguished as a bearer of the surname Cho.
-
A.
Min Hye-jin
Min Hye-jin is a determined and principled lawyer in the South Korean dark fantasy series "Hellbound," who challenges a powerful cult and supernatural decrees of damnation.
-
B.
Jang Hye-jin
Jang Hye-jin is a South Korean actress best known internationally for her role as the resourceful housekeeper in the Academy Award–winning film "Parasite."
-
C.
Jeong Ji-hyun
Jeong Ji-hyun is a Korean individual whose name is romanized from the Korean name Ji-hyun Jung.
-
D.
Cho Hee-yeon
Cho Hee-yeon is a South Korean educator and academic known for serving as the superintendent of the Seoul Metropolitan Office of Education.
-
E.
Suh Ji-hyun
Suh Ji-hyun is a South Korean individual notable for bearing the Korean surname Suh.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6790c935881908f901d058e6a83a9 |
completed | April 20, 2026, 7:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09ad4729d8819085c5e5511a5239fb |
completed | May 17, 2026, 11:57 a.m. |
| NEDg | Description generation | batch_6a09ade09c0081908ec1962de430a6e8 |
completed | May 17, 2026, noon |
| NED2 | Entity disambiguation (via description) | batch_6a09ae91d9cc8190a677124f1a0e1e4e |
completed | May 17, 2026, 12:03 p.m. |
Created at: April 16, 2026, 11:28 a.m.